A novel mathematical model describing adaptive cellular drug metabolism and toxicity in the chemoimmune system

PLoS One. 2015 Feb 20;10(2):e0115533. doi: 10.1371/journal.pone.0115533. eCollection 2015.

Abstract

Cells cope with the threat of xenobiotic stress by activating a complex molecular network that recognizes and eliminates chemically diverse toxic compounds. This "chemoimmune system" consists of cellular Phase I and Phase II metabolic enzymes, Phase 0 and Phase III ATP Binding Cassette (ABC) membrane transporters, and nuclear receptors regulating these components. In order to provide a systems biology characterization of the chemoimmune network, we designed a reaction kinetic model based on differential equations describing Phase 0-III participants and regulatory elements, and characterized cellular fitness to evaluate toxicity. In spite of the simplifications, the model recapitulates changes associated with acquired drug resistance and allows toxicity predictions under variable protein expression and xenobiotic exposure conditions. Our simulations suggest that multidrug ABC transporters at Phase 0 significantly facilitate the defense function of successive network members by lowering intracellular drug concentrations. The model was extended with a novel toxicity framework which opened the possibility of performing in silico cytotoxicity assays. The alterations of the in silico cytotoxicity curves show good agreement with in vitro cell killing experiments. The behavior of the simplified kinetic model suggests that it can serve as a basis for more complex models to efficiently predict xenobiotic and drug metabolism for human medical applications.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • ATP-Binding Cassette Transporters / physiology
  • Computer Simulation
  • Drug Resistance
  • Humans
  • Inactivation, Metabolic*
  • Inhibitory Concentration 50
  • Kinetics
  • Models, Biological*
  • Systems Biology

Substances

  • ATP-Binding Cassette Transporters

Grants and funding

This work was supported by Momentum (“Lendület”) Program of the Hungarian Academy of Sciences (http://mta.hu/articles/momentum-program-of-the-hungarian-academy-of-sciences-130009; GS), the Hungarian Scientific Research Fund (http://www.otka.hu/en; OTKA 83533 to BS; OTKA 111678 to TH), and the Hungarian Research and Technology Innovation Fund (“Kutatási és Technológiai Innovációs Alap“; KTIA-AIK-12-2012-0025; http://ktia.kormany.hu/; TH). TH is a Bolyai Fellow of the Hungarian Academy of Sciences. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.